Results 21 to 30 of about 3,042,023 (186)

COMPUTER SIMULATION OF π – π INTERACTIONS OF TETRATHIOPHENE MOLECULES

Физико-химические аспекты изучения кластеров, наноструктур и наноматериалов, 2021
The properties of the supramolecular organization of conjugated polymers strongly affect the mobility of charge carriers and, consequently, the properties of produced electronic devices based on them.
V.G. Alekseev, P.O. Baburkin, S.-H. Tung, P.V. Komarov   +3 more
doaj   +1 more source

The Effect of Input Parameter Variation on the Accuracy of a Vanadium Redox Flow Battery Simulation Model

Batteries, 2021
Accurately predicting battery behavior, while using low input data, is highly desirable in embedded simulation architectures like grid or integrated energy system analysis. Currently, the available vanadium redox flow battery (VRFB) models achieve highly
Christina Zugschwert, Jan Dundálek, Stephan Leyer, Jean-Régis Hadji-Minaglou, Juraj Kosek, Karl-Heinz Pettinger   +5 more
doaj   +1 more source

Self-Directed Learning [PDF]

, 2021
This book on self-directed learning (SDL) is devoted to original academic scholarship within the field of education, and is the 6th volume in the North-West University (NWU) SDL book series. In this book the authors explore how self-directed learning can
Mzuza, Maureen K., Bailey, Roxanne, du Toit-Brits, Charlene, Sebotsa, Tswakae, Kriek, Jeanne, Olivier, Jako, Fleisher, Steven C., Mahlaba, Sfiso C., Wirth, Karl R., Bergamin, Per, Dhakulkar, Amit, Nuhfer, Edward B., Dudu, Washington T., Jagals, Divan, Sebatana, Motlhale J., Watson, Rachel, Chahine, Iman C., Blignaut, Henry, de Beer, Josef   +18 more
core   +1 more source

Efficient generation of stable linear machine-learning force fields with uncertainty-aware active learning

Machine Learning: Science and Technology, 2023
Machine-learning (ML) force fields (FFs) enable an accurate and universal description of the potential energy surface of molecules and materials on the basis of a training set of ab initio data.
Valerio Briganti, Alessandro Lunghi
doaj   +1 more source

Multiresolution image parametrization for improving texture classification [PDF]

, 2008
In the paper an innovative alternative to automatic image parametrization on multiple resolutions, based on texture description with specialized association rules, and image evalu- ation with machine learning methods is presented.
Igor Kononenko, Kononenko, Igor, Šajn, Luka, Luka Šajn   +3 more
core   +1 more source

Generation of Lagrangian intermittency in turbulence by a self-similar mechanism

New Journal of Physics, 2013
Intermittency, i.e., extreme fluctuations at small scales, causes the deviation of turbulence statistics from Kolmogorov's 1941 theoretical predictions. Intermittency effects are especially strong for Lagrangian statistics.
Michael Wilczek, Haitao Xu, Nicholas T Ouellette, Rudolf Friedrich, Eberhard Bodenschatz   +4 more
doaj   +1 more source

Resonance enhancement of dark matter interactions: the case for early kinetic decoupling and velocity dependent resonance width

Journal of High Energy Physics, 2017
Motivated by the possibility of enhancing dark matter (DM) self-scattering cross-section σ self , we have revisited the issue of DM annihilation through a Breit-Wigner resonance.
M. Duch, B. Grzadkowski
doaj   +1 more source

Quantitative 3D Reconstruction from Scanning Electron Microscope Images Based on Affine Camera Models

Sensors, 2020
Scanning electron microscopes (SEMs) are versatile imaging devices for the micro- and nanoscale that find application in various disciplines such as the characterization of biological, mineral or mechanical specimen.
Stefan Töberg, Eduard Reithmeier
doaj   +1 more source

Nonlinear dynamics of self-, parametric, and externally excited oscillator with time delay: van der Pol versus Rayleigh models [PDF]

Nonlinear Dynamics, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Statistical learning of protein elastic network from positional covariance matrix

Computational and Structural Biotechnology Journal, 2023
Positional fluctuation and covariance during protein dynamics are key observables for understanding the molecular origin of biological functions. A frequently employed potential energy function for describing protein structural variation at the coarse ...
Chieh Cheng Yu, Nixon Raj, Jhih-Wei Chu
doaj   +1 more source